VANCOUVER, BC: Canadian optimization software company, Clir Renewables has secured its first project in France following the recent opening of its first office in Europe. The client, a GW scale owner-operator in the region has chosen Clir to support optimizing the performance of their current wind portfolio.

Having considered other providers in the market, Clir was chosen by the owner specifically due to the system’s ability to provide actionable items to increase production and hold the OEM to account.

France offers an excellent opportunity for Clir Renewables to expand its reach within Europe. At the end of 2017, France Energie Eolienne reported there was 13.5 GW of onshore wind installed. In 2018 the French Government released their Multiannual Energy Programme (programmation pluriannuelle de l’énergie, PPE) laying out their energy transition to a cleaner energy mix, including plans to triple installed onshore wind capacity by 2030. This commitment to onshore wind shows the market is strong and will grow steadily over the coming decade.

Craig McCall, Director of Europe “In recent years we have seen a shift in owners focusing more on their operational assets in France. A significant contributor to this shift is due to the recently imposed regulatory requirements surrounding noise impact in 2011. The change allows the undertaking of a new noise impact assessment at any point either as a result of a residential complaint or ICPE inspection. This leaves many owners exposed as non-compliance of a wind farm can be revealed after several years of operation.

It’s great to see a large owner-operator in the region having the confidence to bring on Clir despite having their own extremely competent team of engineers. Our view as a business has always been to provide clients with the tools to conduct analysis quickly and at scale to optimize their assets.

Using Clir allows owners to bypass time-consuming analysis by clearly quantifying the impact of all potential areas of underperformance. This allows their technical teams to focus on implementing the performance improvement measures that have the highest return on investment, as opposed to getting caught up trying to make sense of the poorly structured data provided by the OEM’s.”

About Craig McCall: Craig has over six years’ experience in the renewable energy industry and most recently led a world-leading renewable energy technical consultants Optimisation and Control service line. To date, Craig has been involved in more than 50 wind farm optimization projects across Europe, Asia, and the Americas.

In 2017, North American Electric Reliability Corporation (NERC) introduced GADS-W reporting. It was only in 2018 that the NERC made the GADS reporting mandatory for wind farms with 200 MW or greater total installed capacity. This year there are new requirements. As of January 1, 2019 operators of wind farms with 100 MW or greater total installed capacity are required to compile reports on a monthly basis and submit those reports to NERC each quarter. And sites of greater than 75 MW will be required to report from January 1, 2020.

With less than a month to submit the Q4 2018 GADS report, analysts across North America are scrambling to find time to prepare reports to meet the February 15 deadline.

Operators are required to submit two reports. First, the Performance Data Report, which summarizes overall wind turbine operation in a particular month. Second, the Component Outage Report which identifies the area or reason for lost production as reported in the Performance Data Report. NERC uses the information in these reports to calculate wind farm performance, reliability, and availability statistics. The requirements in producing these reports are challenging with complex rules and conditions that must be considered when allocating downtime to appropriate GADS-W reporting categories.

For many wind farms the data streams available to operators to produce these reports, e.g. OEM SCADA, are not set up or designed to comply with GADS-W reporting directly. Also, operators generally don’t have the tools to process their available data streams. These structural challenges leave operators faced with the periodic, time-consuming and complicated task of manually processing and editing available data streams to try and produce GADS-W reports. To address these specific challenges, Clir Renewables has developed a GADS-W Reporting tool which makes generating and submitting reports to NERC a straightforward task.

Leveraging Clir’s industry-leading proprietary data model, the software processes turbine SCADA data streams to seamlessly and automatically produce GADS-W reports, ready for submission to NERC, at the click of a button. It is a collection of functions working together that produce the one-click report. How does it all work? Firstly, SCADA data is processed by Clir to identify and categorize wind turbine downtime and lost energy accurately. Clients can then interact with the software to edit default allocations, a functionality we call ‘error code reconciliation’, to ensure downtime is accurately categorized. In addition, Clir has developed software to ingest documents like service reports, to ensure the reasons for downtime and lost production are accurately described on the platform. Clir’s software also identifies sequences of status codes automatically grouping these into outages enabling easier editing of event allocations and maps status codes to the appropriate default GADS-W reporting allocation. All of these functions drastically reduce the amount of time required in preparing GADS-W reports.

Dr. Shane Butler, Data Scientist at Clir, stated, “Generating the monthly reports on a quarterly basis is a time-consuming and onerous task for an operator to produce. Mistakes due to human error and misunderstandings in allocating downtime can be expected when dealing with such large amounts of data, especially at larger wind farms.

“Using Clir’s software to process the data required for GADS-W reports, not only reduces the time required but also ensures greater accuracy,” Butler continued.

In 2018 Clir Renewables’ clients with wind farms over 200 MW of installed capacity utilized the Clir GADS-W Reporting tool to produce their reports, easily meeting each deadline and will do so again for the February 15 deadline for the final quarter of the 2018 production year. Feedback on the tool was all positive, with clients telling of their delight at the ease with which the reports are produced and the amount of time saved against manual production of the reports.

Deadlines for the 2019 production year are May 15 for the first quarter, August 15 for the second quarter, November 15 for the third quarter and February 15, 2020, for the fourth quarter, mark them in the calendar now.

About Dr. Shane Butler: Shane is a recognized industry expert in the application of data science skills to real-world problems to enable and support informed decision making. For the past five years, Shane has been applying his big data analytics skill set within the domain of wind farm operations, performance analytics, and predictive maintenance. Expert user of Matlab, Python, Tableau, and Cloud-based computing platforms.

As wind turbine design advances and existing fleets age, there is a case to be made for implementing system upgrades, but how do you know if it is worth the initial investment?

VANCOUVER, BC: Clir Renewables has released a new software feature to support the validation of turbine upgrades. Whether it is a software or hardware upgrade validation needn’t only be theoretical.

As the design of wind turbines advances reviewing the performance of the existing fleet can highlight areas where improvements can be made by upgrading the current hardware or software. Original Equipment Manufacturers (OEMs) and third-party companies are regularly offering owners ways to improve the performance of current turbines. These upgrades can be physical changes to the turbine like aerodynamic enhancements such as vortex generators, gurney flap or leading edge tape. Software-based changes could include new blade pitching algorithms, improved yaw control or increased cut-out and re cut-in wind speeds. Loads on turbine components may be increased, depending on the nature of the upgrade. The benefit of increased Annual Energy Production (AEP) should be carefully weighed against the implications of increased loading.

As owners know, no two sites are the same so how can they be sure investing in these upgrades will increase AEP? By validating the impact of the upgrade against the claimed gain by the manufacturer. However, independent validation studies on specific upgrade options are scarce, or not applicable to every site. Without independent validation, owners may never know the true benefit of making the upgrade.

Independent validation is possible by implementing the upgrade on a small percentage of turbines on site, assessing the impact on AEP and evaluating it against the investment required to install the upgrade across the whole farm. Clir software has the most advanced data model in the industry which makes this validation easier to complete than via traditional methods. By integrating SCADA, CMS, meteorological, geospatial data and much more to build predictive models of turbine behaviour, Clir software can identify changes in a turbine’s performance and benchmark it against numerous models. An assessment of the cost-benefit of the potential upgrade is then performed before full implementation.

Additionally, Clir Renewables has extensive knowledge of upgrades offered by OEMs. The data science team has conducted in-depth reviews of documentation provided by OEMs as well as contributed to conversations about upgrade implementation at many wind farm sites. Clir Renewables provides independent and impartial information based on site-specific data and OEM documents.

Andrew Brunskill, Data Scientist at Clir Renewables, said “There are few simple answers to turbine upgrades as comparing two wind farm sites to each other is like comparing an apple to an orange.

“The impact of each upgrade on energy production and turbine loads depends on the local wind climate and the specific turbine model in use at the site, among other factors, that’s why independent validation is important,” Brunskill continued.

By using Clir software to validate upgrades owners avoid expensive consultancy fees and have the information to negotiate confidently with the OEM or third-party company on the cost.

About Andrew Brunskill: Andrew is a PEng from a major global consultancy and has taken on a wide variety of roles during his career including project engineer, energy analyst, modeling specialist, and project manager. In recent times he has undertaken performance analytics across Vestas, Siemens, GE, Suzlon, and Siemens wind turbine technology.

VANCOUVER, BC: Clir Renewables has developed renewable optimization and reporting software to quantify the impacts of forestry on wind farms. The impact of forestry on inflow conditions is often poorly accounted for when developing wind farms, and once a project is operating, there can be a significant physical effect on the life expectancy of the turbines and an adverse effect on performance.

For wind farm owners, wind turbine blades effortlessly gliding through the air when met by smooth, undisturbed inflow conditions is easy on the equipment. However, projects situated in or near forested terrain typically present additional challenges. As the wind passes over forestry canopies, wind flow is disturbed, generating more complex conditions such as turbulence and shear, creating slower uneven loads on the blades. This turbulent air stresses the blades in differing proportions increasing the level of wear and tear across wind turbine, including but not limited to accelerated blade cracking and gearbox and generator failures, reducing life expectancy.

Until now owners have not had the tools to quickly and easily understand the impact of forestry at a wind farm, often relying on often prohibitive, expensive studies to assess the impact. Clir software is built on a domain-specific data model that takes account of geospatial considerations, such as forestry, that drive turbine inflow conditions. By utilizing the geospatial information and atmospheric stability, performance issues at the turbine itself, and in the inflow conditions, can be more accurately parsed out to enable owners, operators and other wind farm stakeholders to understand project underperformance and performance risk for specific items such as forestry.

“Many owners are likely experiencing generation losses due to forestry in the area of their wind farms; the degree to which they may be unaware. Additionally, the disturbed wind inflow may be increasing turbine loading, reducing their operational life. Additional operational costs associated with premature component failures and reduced turbine service life can surprise owners who may not have accounted for this in their financial model,” said Andrew Cameron, Data Scientist at Clir Renewables.

“By assessing this early in the wind farm’s operational life many of the costs and losses can be better understood, accounted for and potentially reduced.” Andrew continued.

Once an owner is aware of the forestry impact on AEP and loading conditions, a cost-benefit analysis can be formulated to identify the appropriate next steps. When implemented the optimization recommendations can produce increases of around 5% AEP for the wind farm and extend asset life by up to five years. In situations where a wind farm’s forestry is poorly managed gains of almost 10% AEP, and 5+ years of life extension are possible.

Clir CEO Gareth Brown says: “The wind industry is unique. It’s the only power source we don’t know what the inflow conditions are. The industry to date has tried to build digital and physics-based models, but they are limited in scope and capabilities as they fail to take into account the inflow conditions. By digitizing beyond an individual turbine and what drives their inflow conditions enables Clir to more accurately build effective advanced analytics and AI tools to identify where performance can be improved.”

Brown continues, “The challenges defining performance issues due to no inflow measurement are compounded by, poorly structured SCADA data, inadequate industry performance tools and metrics that focus on the question is the turbine spinning rather than performing, and conflicted service providers or OEMs who are focused on protecting their internal know-how rather than building products to enable effective performance management. The Clir platform circumvents this by building a domain-specific data model that gives owners the tools to maximize their understanding of the asset, where lost energy is occurring and get clear actions to mitigate the lost energy for items like forestry and many others.”

About Andrew Cameron: Andrew has a masters degree in mechanical engineering and over ten years’ experience in the wind energy industry. His expertise includes both pre-construction analysis as well as operational analysis for a wide variety of wind regimes, turbine technologies, data collection techniques, and analysis goals.

Blade icing has a major impact on wind turbines but has historically been difficult to assess. Clir Renewables developed software to detect icing and reduce associated losses.

VANCOUVER, BC: Clir Renewables has released a new software feature which detects icing on turbine blades and measures its impact on performance. Weather is uncontrollable but assessable, and that’s what is required when mitigating icing impacts.

There are thousands of wind turbines located in cold and icing climates around the world and the estimated market potential for wind farms in cold and icing climate is over 200 GW*. Losses due to icing can range from a few percentage points all the way up to over 40% during the icing season. Blade icing furthermore causes increased loads and reduced aerodynamics, as well as health and safety concerns. Most of the time icing isn’t included in warranties or service contracts meaning the effects are difficult for owners to quantify. A simple SCADA data analysis often isn’t sufficient and it takes sophisticated analysis to pinpoint icing occurrences and quantify losses. Owners are looking for means to quantify losses and make the investment case for icing mitigation systems, but often don’t have the required information to do so.

Clir recognized this gap in information and developed a solution to automatically detect icing and quantify the associated losses. The algorithm uses a probability analysis approach to flag deviations from historical, turbine-specific power curves, based on site-specific climatic conditions and historical icing events. The icing events are automatically flagged to the useras a part of our standard system, including the losses related to the events, which enables the users to make informed decisions on how to proceed. The method is based on IEA Task 19’s standardized and widely approved method for ice loss calculations^ and has been further refined within the Clir system. Based on the results from the algorithm, Clir can make recommendations for optimization when the wind farm is experiencing icing. As part of this optimization work, an evaluation of any installed ice detection and mitigation system is undertaken, and the results are also useful for the evaluation of available third-party alternatives.

Rebecka Klintström, Data Scientist at Clir Renewables, says, “Significant losses are often experienced at wind farms in cold climates due to the impact of icing, but it is possible to regain some of this when there is a better understanding of the situation. With all the information, owners have the ability to take action and improve their output. One owner saw an increase of almost 5 % AEP after a manufacturer control update was implemented following assessment by Clir. While not all sites will see such an increase, it shows that icing is an issue that needs investigation.”

When it comes to decision making, knowledge is power and this what Clir’s software provides its users. The benefits to owners, operators and site managers of having this information are the quantification of the losses incurred, evidence for the manufacturer to optimize control algorithms, and decision-support for potential investment in a third-party ice mitigation system.

“Icing loss issues are compounded as they are excluded from the contractual obligations of the OEMs or the service providers under most service contracts. This has meant the issue has not been well managed in the turbine control design or operation phase of the assets, said Clir CEO, Gareth Brown.

“The Clir software has given owners actionable insights to increase output by reducing the number of false positive shutdowns inherent in the control assumptions for health and safety and loads on the blade. It also helps owners build the business case to change the control strategy of turbines and potentially shutdown turbines during icing conditions (freezing clouds) to minimize the build-up of ice on blades. The data model is set up specifically for renewables and Clir is the only platform in the market which can handle these types of issues,” he added.

About Rebecka Klintström: Rebecka has over six years’ experience working in the wind industry, both as a consultant and for a utility. She has worked in all phases of a wind project, from pre-construction flow modeling, met mast installations and noise modeling to operational analysis, icing loss modeling, and optimizations, as well as managed research projects and project portfolios. Rebecka was a member of IEA’s task 19 for over five years and has an active role in developing the ice detection and loss algorithms. She’s been at Clir from the start and has worked with most turbine technologies, as well as starting up and heading Clir’s Inclusion and Diversity initiative.

VANCOUVER, BC: With installed wind energy capacity now over 539 GW*, many turbines are reaching the mid to late stage of their operational life expectancy. Typically wind turbines have an operational life expectancy of 20 years, but many only operate for the duration of the Power Purchase Agreement (PPA) under which they were constructed, sometimes just 15 years. Creating a strategic plan for asset life extension is critical for efficient management of wind farms. Clir Renewables recently launched a new product feature that allows for variable scenario analysis to determine the best way to operate assets.

As turbines age, owners and operators more urgently need to know how long their turbines are going to last. They often end up setting aside increasing amounts of budget for unplanned maintenance to ensure the asset is operating in a safe and profitable manner as various components approach the end of their design life. However, an in-depth analysis of turbine data allows for the creation of strategic maintenance plans. These maintenance plans are created to prevent unexpected component failures and extend the operational life of the turbines. This is often undertaken as a one-off study assessing existing site data which can’t take into consideration true site conditions of the future. Clir Renewables has tackled the industry issue of life extension analysis by developing detection tools enabling clients to assess and quantify the potential for life extension of their assets beyond 20 years and provide guidance for their maintenance planning.

Clir’s software regularly analyses wind farm data, providing clients clear access to the information they need to make operational decisions in real time. Analytical models consider a wide range of data, including wind flow conditions, component temperatures, and vibrational data. Each data set is then compared to the turbine design and loading parameters to quantify the operational risks turbines and individual components are exposed to. The software takes design loading conditions on a certification and site basis, compares it to real-world conditions derived from turbine data to quantify what risks turbines are exposed to and to what degree the turbines are operating within themselves. This understanding gives Clir’s clients actionable information to assist in long-term strategic maintenance planning and avoid unexpected component failures.

With Clir’s software, continual assessment of component health ensures owners and operators are better informed about the condition of their assets and can build operational strategies in line with their long-term plans. The data can be fed into financial models, O&M strategies and assist in deciding whether to ‘sweat’ the assets during the PPA or extend their operational life past the agreement.

“Using automated algorithms and machine learning to assess wind turbine performance is an important advancement in the optimization of the wind industry. Continually assessing multiple data points across a site or portfolio means decisions are based on up-to-date rather than historical data. Better informed decisions reduce risk which can only be positive”, said Selena Farris, Data Scientist at Clir Renewables.